Image stitching method and related monitoring camera apparatus

ABSTRACT

An image stitching method applied to a monitoring camera apparatus with a first image receiver and a second image receiver for acquiring a first image and a second image. The image stitching method includes detecting a plurality of first features in the first image and a plurality of second features in the second image, dividing the plurality of first features at least into a first group and a second group and further dividing the plurality of second features at least into a third group, analyzing the plurality of first features and the plurality of second features via an identification condition to determine whether one of the first group and the second group is matched with the third group, and utilizing two matched groups to stitching the first image and the second image.

BACKGROUND OF THE INVENTION 1. Field of the Invention

The present invention relates to an image stitching method and amonitoring camera apparatus, and more particularly, to an imagestitching method utilizing a feature without an identification patternto increase a detecting distance and systemic adaptability and a relatedmonitoring camera apparatus.

2. Description of the Prior Art

If a monitoring camera is applied for capturing a large-range monitorimage, several camera units are arranged in different angles to face amonitoring region of the monitoring camera. A field of view of onecamera unit is different from a field of view of any other cameras. Anedge of the field of view of one camera unit can be partly overlappedwith an edge of the field of view of the adjacent camera unit.Conventional image stitching technology can set some marking features inan overlapped region of the monitoring images, and the marking featuresin the overlapped region can be used to stitch small-range images forgenerating the large-range image. The marking feature has a specialidentification pattern, so that the monitoring camera can determine thestitching direction and stitching sequence of the monitoring images viathe identification pattern. A drawback of the conventional imagestitching technology is a limited installation height of the cameraunit. If the camera unit is disposed on a location higher than anallowable height, the camera unit cannot identify whether the markingfeatures in the plurality of monitoring images have the sameidentification pattern. Design of an image stitching method of using themarking feature without the identification pattern and increasing itsdetectable distance is an important issue in the monitoring industry.

SUMMARY OF THE INVENTION

The present invention provides an image stitching method utilizing afeature without an identification pattern to increase a detectingdistance and systemic adaptability and a related monitoring cameraapparatus for solving above drawbacks.

According to the claimed invention, an image stitching method is appliedto a monitoring camera apparatus with a first image receiver and asecond image receiver for respectively acquiring a first image and asecond image. The image stitching method includes detecting a pluralityof first features in the first image and a plurality of second featuresin the second image, dividing the plurality of first features at leastinto a first group and a second group and further dividing the pluralityof second features at least into a third group, analyzing the pluralityof first features and the plurality of second features via anidentification condition to determine whether one of the first group andthe second group is matched with the third group, and utilizing twomatched groups to stitch the first image and the second image.

According to the claimed invention, a monitoring camera apparatus withan image stitching function includes a first image receiver, a secondimage receiver and an operational processor. The first image receiver isadapted to acquire a first image. The second image receiver is adaptedto acquire a second image. The operational processor is electricallyconnected to the first image receiver and the second image receiver. Theoperational processor is adapted to detect a plurality of first featuresin the first image and a plurality of second features in the secondimage, divide the plurality of first features at least into a firstgroup and a second group and further dividing the plurality of secondfeatures at least into a third group, analyze the plurality of firstfeatures and the plurality of second features via an identificationcondition to determine whether one of the first group and the secondgroup is matched with the third group, and utilize two matched groups tostitch the first image and the second image.

The first feature and the second feature used in the image stitchingmethod of the present invention do not have special identificationpattern, so that the image stitching method and the related monitoringcamera apparatus can increase its detectable distance and detectablerange. The image can be stitched with one image or a plurality ofimages, and the features detected in the image can be used for stitchingwith one image or be divided for stitching several images. Thus, theimage stitching method of the present invention can divide the featuresin each image into one or more groups, and then match the groups betweendifferent images for finding out the groups that are useful in imagestitching. After the group matching, the image stitching method can pairthe features between the matched groups and compute the relatedtransformation parameter via the paired features. The images can bestitched via the paired features and the transformation parameter.

These and other objectives of the present invention will no doubt becomeobvious to those of ordinary skill in the art after reading thefollowing detailed description of the preferred embodiment that isillustrated in the various figures and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a functional block diagram of a monitoring camera apparatusaccording to an embodiment of the present invention.

FIG. 2 is a diagram of images acquired by the monitoring cameraapparatus according to the embodiment of the present invention.

FIG. 3 is a flow chart of the image stitching method according to theembodiment of the present invention.

FIG. 4 to FIG. 8 are diagrams of image stitching recording according tothe embodiment of the present invention.

FIG. 9 is a diagram of the image stitching recording according toanother embodiment of the present invention.

DETAILED DESCRIPTION

Please refer to FIG. 1 and FIG. 2. FIG. 1 is a functional block diagramof a monitoring camera apparatus 10 according to an embodiment of thepresent invention. FIG. 2 is a diagram of images acquired by themonitoring camera apparatus 10 according to the embodiment of thepresent invention. The monitoring camera apparatus 10 can include someimage receivers and an operational processor 12; the present inventiongives an example of a first image receiver 14 and a second imagereceiver 16, and an actual application is not limited to the foresaidapplication. The monitoring camera apparatus 10 may have three or moreimage receivers. A field of view of the first image receiver 14 ispartly overlapped with a field of view of the second image receiver 16.The first image receiver 14 and the second image receiver 16 canrespectively acquire a first image I1 and a second image I2. Theoperational processor 12 can be electrically connected with the firstimage receiver 14 and the second image receiver 16 in a wire manner orin a wireless manner. The operational processor 12 can execute an imagestitching method of the present invention to stitch the first image I1and the second image I2. The operational processor 12 can be a built-inunit of the monitoring camera apparatus 10 or an external unit, whichdepends on actual demand.

Please refer to FIG. 1 to FIG. 8. FIG. 3 is a flow chart of the imagestitching method according to the embodiment of the present invention.FIG. 4 to FIG. 8 are diagrams of image stitching recording according tothe embodiment of the present invention. The image stitching methodillustrated in FIG. 3 can be suitable for the monitoring cameraapparatus 10 shown in FIG. 1. For the image stitching method, step S300can be executed to transform the first image I1 and the second image I2into binary forms for detecting a plurality of first features F1 in thebinary first image I1 and a plurality of second features F2 in thebinary second image I2, as shown in FIG. 4. Generally, the first featureF1 and the second feature F2 are human-made features, and can be athree-dimensional object with a specific shape or a two-dimensionalprinted pattern with a specific appearance, which depend on a designdemand. If the first image I1 and the second image I2 are arrangedhorizontally, the first feature F1 and the second feature F2 can bemainly disposed on a right side and a left side of each image. If thefirst image I1 and the second image I2 are arranged vertically, thefirst feature F1 and the second feature F2 can be disposed on an upperside and a lower side of each image. An application about the imagesarranged side-by-side in a horizontal direction is illustrated asfollowing.

The first feature F1 and the second feature F2 can be the geometricpattern with any shapes, such as a circular form, or a polygon formsimilar to a triangular form or a rectangle form. The image stitchingmethod may detect the fully geometric pattern for identification.Besides, the first feature F1 and the second feature F2 can be thespecific pattern defined by a user, such as an animal pattern, or anobject pattern similar to a vehicle or a building. The image stitchingmethod may detect the fully specific pattern for identification; theimage stitching method further may detect a partial region of thespecific pattern, such as a face of the animal pattern or a top or abottom of the object pattern, for identification.

Then, step S302 can be executed to divide the plurality of firstfeatures F1 and the plurality of second features F2 into several groups.As an example of the first image I1, the image stitching method maychoose one of the plurality of first features F1, such as a firstfeature F1 a shown in FIG. 5, and then compute an interval D1 betweenthe first feature F1 a and a first feature F1 b, an interval D2 betweenthe first feature F1 a and a first feature F1 c, and an interval D3between the first feature F1 a and a first feature F1 d. The imagestitching method can set or acquire the threshold from a memory (notshown in the figures) of the monitoring camera apparatus 10. Theintervals D1, D2 and D3 can be respectively compared with the threshold.The threshold is used to classify the plurality of features intodifferent groups, and can be manually set by the user or automaticallyset by a system. The threshold can be set according to a dimension ofthe image or the interval between the features. For example, the minimalinterval D1 can be selected from the intervals D1, D2 and D3. Theminimal interval D1 can be weighted to define as the threshold, so thatthe threshold can be dynamically decided according to the minimalinterval between any two features in the images for conforming to anautomatic design trend. A weighting value mentioned above can be, butnot limited to, greater than 1.0. According to foresaid embodiment, thethreshold may not be preset by the user, and the monitoring cameraapparatus 10 can automatically generate the threshold, which conforms toan actual situation, in accordance with the detected interval betweenthe features when the weighting value is set; the above-mentioned designcan provide preferred tolerance and convenience for disposing thefeatures, and better advance operation of the image stitching method.

The minimal interval D1 not only can be a base of the threshold, butalso can be a counting unit of the intervals D2 and D3. For example, ifthe interval D1 between the first feature F1 a and the first feature F1b is defined as one unit length, the interval D2 between the firstfeature F1 a and the first feature F1 c may be represented as four timesthe interval D1 (which means four unit lengths), and the interval D3between the first feature F1 a and the first feature F1 d may berepresented as five times the interval D1 (which means five unitlengths). A ratio about the unit length of the intervals D2 and D3 tothe interval D1 depends on the actual demand.

In step S302, the first feature F1 a may be defined as belonging to thefirst group G1, and the intervals D1, D2 and D3 can be respectivelycompared with the threshold. If the interval D1 is smaller than or equalto the threshold, the first feature F1 b can belong to the first groupG1 with the first feature F1 a; if the intervals D2 and D3 are greaterthan the threshold, the first features F1 c and F1 d can be differentfrom the first feature F1 a and belong to the second group G2 (anothergroup opposite to the first group G1), as shown in FIG. 6. In theembodiment, a right side and a left side of the first image I1 can berespectively stitched with the second image I2 and another image (notshown in the figures), so that the first features F1 can be divided intoat least two groups. If three side of the first image I1 arerespectively stitched with three images, the first features F1 can bedivided into three or more groups. The second features F2 can be dividedat least into a third group G3 and a fourth group G4, which is similarto a dividing method about the first features F1, and a detaileddescription is omitted herein for simplicity.

In the embodiment shown in FIG. 6, if the first feature F1 a is definedas belonging to the second group G2, the first feature F1 b having theinterval D1 smaller than or equal to the threshold can belong to thesecond group G2 with the first feature F1 a. The first features F1 c andF1 d have the intervals D2 and D3 greater than the threshold, and can bedifferent from the first feature F1 a and belong to the first group G1.A serial number of the group whereto the features belong may follow inproper order or be decided by the user, which depends to an applicabledemand.

As an example of the first image I1, group dividing is used to classifysome first features F1 (such as the first features in the second groupG2) matched with the second image I2 and other first features F1 (suchas the first features in the first group G1) matched with another imagefor stitching, so that the first group G1 and the second group G2 of thefirst image I1 can respectively located at different regions in thefirst image I1. The different regions may be the right side and the leftside, or the upper side and the lower side of the first image I1, whichdepend on a source and an aim of the stitching image. The third group G3and the fourth group G4 are respectively located at different regions inthe second image I2, and used to match with the first image I1 andanother image (not shown in the figures) for stitching.

Then, step S304 can be executed to analyze the plurality of firstfeatures F1 and the plurality of second features F2 via anidentification condition for determining whether one of the first groupG1 and the second group G2 can be matched with the third group G3 or thefourth group G4. The identification condition can be selected from agroup consisting of color, a dimension, a shape, an amount, anarrangement and a combination of the plurality of first features F1 andthe plurality of second features F2. In an example of color features, ifthe first features F1 a and F1 b in the first group G1 are red, and thefirst features F1 c and F1 d in the second group G2 are blue, and thesecond features F2 in the third group G3 are blue, and the secondfeatures F2 in the fourth group G4 are yellow, the image stitchingmethod can rapidly determine that the second group G2 is matched withthe third group G3 via analysis of the color features.

In an example of dimension and shape features, if the first features F1a and F1 b in the first group G1 are small circular spots, and the firstfeatures F1 c and F1 d in the second group G2 are middle square blocks,and the second features F2 in the third group G3 are the middle squareblocks, and the second features F2 in the fourth group G4 are largetriangle forms, the image stitching method can rapidly determine thatthe second group G2 is matched with the third group G3 via geometricanalysis of the features. In an example of arrangement features, if thefirst features F1 a and F1 b in the first group G1 are verticalarrangement, and the first features F1 c and F1 d in the second group G2are transverse arrangement, and the second features F2 in the thirdgroup G3 are the transverse arrangement, and the second features F2 inthe fourth group G4 are oblique arrangement, the image stitching methodcan rapidly determine that the second group G2 is matched with the thirdgroup G3 via arrangement analysis of the features. In an example ofamount features, if an amount of the first features F1 in the secondgroup G2 is identical with an amount of the second features F2 in thethird group G3, but different from an amount of the second features F2in the fourth group G4, the image stitching method can determine thesecond group G2 is matched with the third group G3.

It should be mentioned that even though the plurality of featuresconforms to the same arrangement, intervals between the plurality offeatures still can be used to determine matching of those groups. Ifsome first features F1 and some second features F2 are the transversearrangement, two groups may be considered as not matching because firstintervals between these first features F1 are different from secondintervals between these second features F2, or because a differencebetween the first interval and the second interval exceeds a predefinedthreshold.

If the first group G1 and the second group G2 cannot be matched with thethird group G3 or the fourth group G4, step S306 can be executed thatthe image stitching method determines the first image I1 is not stitchedwith the second image I2. If one of the first group G1 and the secondgroup G2 can be matched with the third group G3 or the fourth group G4,such as the second group G2 being matched with the third group G3, aregion of the second group G2 in the first image I1 and a region of thethird group G3 in the second image I2 can belong to an overlappingregion of the first image I1 and the second image I2, so that step S308can be executed to search at least two first features F1 and at leasttwo second features F2 within the matched groups G2 and G3 for pairingvia the foresaid identification condition. As shown in FIG. 7, the firstfeature F1 c can be paired with the second feature F2 in an upper regionof the third group G3, and the first feature F1 d can be paired with thesecond feature F2 in a lower region of the third group G3.

When group matching is completed, the image stitching method can searchthe first features F1 and the second features F2 for pairing within thematched second group G2 and the matched third group G3 according to thegroup consisting of the color, the dimension, the shape, the amount, thearrangement and the combination thereof. The first features F1 and thesecond features F2 which cannot be paired are not applied for the imagestitching method. Final, steps S310 and S312 can be executed to analyzedifference between the at least two first features F1 and the at leasttwo second features F2 paired with each other for acquiring atransformation parameter, and utilize the transformation parameter tostitch the first image I1 and the second image I2 for generating acombined image I3, as shown in FIG. 8. The image stitching method cancompute the transformation parameter via mean-square error (MSE)algorithm or any other mathematic model.

In the above-mentioned embodiment, when the monitoring camera apparatus10 has three or more image receivers, the image stitching method candivide the plurality of first features F1 and the plurality of secondfeatures F2 at least into two groups, so the first image I1 and thesecond image I2 can be stitched with a left-side image and/or aright-side image. The image stitching method of the present inventionfurther can be applied for a situation of one image stitched with otherimage only via one side. Please refer to FIG. 9. FIG. 9 is a diagram ofthe image stitching recording according to another embodiment of thepresent invention. In this embodiment, the second image receiver 16 canface the field edge of view of the monitoring camera apparatus 10 toacquire the second image I2′, and step S302 in the image stitchingmethod can be executed by setting one group on a side of the secondimage I2′ close to the first image I1, which means the third group G3can be set from a left cluster of the plurality of second features F2. Aright side of the second image I2′ is not stitched with other image, sothat a left cluster of the plurality of second features F2 does not seta group.

Then, following steps can be similar to the above-mentioned embodiment.The image stitching method can determine whether the first group G1 orthe second group G2 in the first image I1 is matched with the thirdgroup G3 in the second image I2′. If the first group G1 is not matchedwith the third group G3, the left side of the first image I1 can bestitched with another image instead of the second image I2′; if thesecond group G2 is matched with the third group G3, the right side ofthe first image I1 can be stitched with the left side of the secondimage I2′.

In one specific embodiment, a monitoring area of the monitoring cameraapparatus 10 may have several features, and the image receiver cannotcapture the image containing all the features due to an angle of view ofthe image receiver. As shown in FIG. 9, the right side of the firstimage I1 captured by the first image receiver 14 only contains two firstfeatures F1, and the left side of the second image I2 captured by thesecond image receiver 16 contains three second features F2. Theright-side second feature F2 is distant from two left-side secondfeatures F2 in the group G2, so the field of view of the first imagereceiver 14 cannot contain all the three second features F2. The imagestitching method can execute step S302 to divide the second features F2in the second image I2 into two groups. The amount of the first featuresF1 in the second group G2 is different from the amount of the secondfeatures F2 in the third group G3, and the color, the dimension and theshape can be used as the identification condition for executing thegroup matching in step S304 and feature pairing in step S308; that is tosay, selection of the color, the dimension, the shape, the amount andthe arrangement of the feature can be varied in different procedures(such as the group matching and the feature pairing), which depends ondesign demand and actual application.

In conclusion, the first feature and the second feature used in theimage stitching method of the present invention do not have specialidentification pattern, so that the image stitching method and therelated monitoring camera apparatus can increase its detectable distanceand detectable range. The image can be stitched with one image or aplurality of images, and the features detected in the image can be usedfor stitching with one image or be divided for stitching several images.Thus, the image stitching method of the present invention can divide thefeatures in each image into one or more groups, and then match thegroups between different images for finding out the groups that areuseful in image stitching. After the group matching, the image stitchingmethod can pair the features between the matched groups and compute therelated transformation parameter via the paired features. The images canbe stitched via the paired features and the transformation parameter.Comparing to the prior art, the image stitching method and themonitoring camera apparatus of the present invention executes the groupmatching firstably, and then executes the feature pairing in accordancewith a result of the group matching, so as to effectively increasediversity of the features, and further to provide preferred stitchingspeed and accuracy.

Those skilled in the art will readily observe that numerousmodifications and alterations of the device and method may be made whileretaining the teachings of the invention. Accordingly, the abovedisclosure should be construed as limited only by the metes and boundsof the appended claims.

What is claimed is:
 1. An image stitching method applied to a monitoringcamera apparatus with a first image receiver and a second image receiverfor respectively acquiring a first image and a second image, the imagestitching method comprising: detecting a plurality of first features inthe first image and a plurality of second features in the second image;dividing the plurality of first features at least into a first group anda second group in accordance with intervals between the plurality offirst features and further dividing the plurality of second features atleast into a third group in accordance with intervals between theplurality of second features; analyzing the plurality of first featuresand the plurality of second features via an identification condition todetermine whether one of the first group and the second group is matchedwith the third group; and utilizing two matched groups to stitch thefirst image and the second image; wherein the plurality of firstfeatures and the plurality of second features are human-made patternsrespectively located inside the first image and the second image;wherein the identification condition is selected from a group consistingof color, a dimension, a shape, an amount, an arrangement and acombination of the plurality of first features and the plurality ofsecond features.
 2. The image stitching method of claim 1, whereindividing the plurality of first features at least into the first groupand the second group comprises: computing several intervals between onefirst feature and other first features of the plurality of firstfeatures; comparing the intervals with a threshold; and determiningwhether each of the plurality of first feature belongs to the firstgroup or the second group according to a comparison result.
 3. The imagestitching method of claim 2, further comprising: setting the thresholddynamically based on a minimal interval of the intervals.
 4. The imagestitching method of claim 2, wherein when one first feature belongs tothe first group, some first features having the interval smaller than orequal to the threshold belong to the first group, and some firstfeatures having the interval greater than the threshold belong to thesecond group.
 5. The image stitching method of claim 1, whereinutilizing the two matched groups to stitch the first image and thesecond image comprises: searching at least two first features and atleast two second features for pairing within the two matched groups viathe identification condition; analyzing difference between the at leasttwo first features and the at least two second features to acquire atransformation parameter; and utilizing the transformation parameter tostitch the first image and the second image.
 6. The image stitchingmethod of claim 5, wherein the image stitching method determines whetherthe first group or the second group is matched with the third group, andthen pairs the first features and the second features of the two matchedgroups via the identification condition.
 7. The image stitching methodof claim 1, wherein the first group and the second group arerespectively located at different regions inside the first image.
 8. Theimage stitching method of claim 1, wherein when the second group ismatched with the third group, a region about the second group in thefirst image and a region of the third group in the second image are anoverlapping region of the first image and the second image.
 9. The imagestitching method of claim 8, wherein the image stitching method utilizesone group of the first group and the second group matched with the thirdgroup to stitch the first image and the second image, and furtherutilizes another group of the first group and the second group to stitchthe first image and another image.
 10. The image stitching method ofclaim 1, wherein the first feature and/or the second feature is ageometric symbol or a specific pattern.
 11. A monitoring cameraapparatus with an image stitching function, comprising: a first imagereceiver adapted to acquire a first image; a second image receiveradapted to acquire a second image; and an operational processorelectrically connected to the first image receiver and the second imagereceiver, the operational processor being adapted to detect a pluralityof first features in the first image and a plurality of second featuresin the second image, divide the plurality of first features at leastinto a first group and a second group in accordance with intervalsbetween the plurality of first features and further dividing theplurality of second features at least into a third group in accordancewith intervals between the plurality of second features, analyze theplurality of first features and the plurality of second features via anidentification condition to determine whether one of the first group andthe second group is matched with the third group, and utilize twomatched groups to stitch the first image and the second image; whereinthe plurality of first features and the plurality of second features arehuman-made patterns respectively located inside the first image and thesecond image; wherein the identification condition is selected from agroup consisting of color, a dimension, a shape, an amount, anarrangement and a combination of the plurality of first features and theplurality of second features.
 12. The monitoring camera apparatus ofclaim 11, wherein the operational processor is further adapted tocompute several intervals between one first feature and other firstfeatures of the plurality of first features, compare the intervals witha threshold, and determine whether each of the plurality of firstfeature belongs to the first group or the second group according to acomparison result.
 13. The monitoring camera apparatus of claim 12,wherein the operational processor is further adapted to set thethreshold dynamically based on a minimal interval of the intervals. 14.The monitoring camera apparatus of claim 12, wherein when one firstfeature belongs to the first group, some first features having theinterval smaller than or equal to the threshold belong to the firstgroup, and some first features having the interval greater than thethreshold belong to the second group.
 15. The monitoring cameraapparatus of claim 11, wherein the operational processor is furtheradapted to search at least two first features and at least two secondfeatures for pairing within the two matched groups via theidentification condition, analyze difference between the at least twofirst features and the at least two second features to acquire atransformation parameter, and utilize the transformation parameter tostitch the first image and the second image.
 16. The monitoring cameraapparatus of claim 15, wherein the operational processor determineswhether the first group or the second group is matched with the thirdgroup, and then pairs the first features and the second features of thetwo matched groups via the identification condition.
 17. The monitoringcamera apparatus of claim 11, wherein the first group and the secondgroup are respectively located at different regions inside the firstimage.
 18. The monitoring camera apparatus of claim 11, wherein when thesecond group is matched with the third group, a region about the secondgroup in the first image and a region of the third group in the secondimage are an overlapping region of the first image and the second image.19. The monitoring camera apparatus of claim 18, wherein the operationalprocessor utilizes one group of the first group and the second groupmatched with the third group to stitch the first image and the secondimage, and further utilizes another group of the first group and thesecond group to stitch the first image and another image.